The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Volatility Computations for Financial Time Series: High Frequency and Hybrid Method

금융시계열 변동성 측정 방법의 비교 분석: 고빈도 자료 및 융합 방법

  • Yoon, J.E. (Department of Statistics, Sookmyung Women's University) ;
  • Hwang, S.Y. (Department of Statistics, Sookmyung Women's University)
  • 윤재은 (숙명여자대학교 통계학과) ;
  • 황선영 (숙명여자대학교 통계학과)
  • Received : 2015.10.01
  • Accepted : 2015.11.26
  • Published : 2015.12.31
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Abstract

Various computational methods for obtaining volatilities for financial time series are reviewed and compared with each other. We reviewed model based GARCH approach as well as the data based method which can essentially be regarded as a smoothing technique applied to the squared data. The method for high frequency data is focused to obtain the realized volatility. A hybrid method is suggested by combining the model based GARCH and the historical volatility which is a data based method. Korea stock prices are analysed to illustrate various computational methods for volatilities.

본 연구에서는 금융시계열 변동성 측정을 위한 다양한 방법들을 소개하고 비교분석 하였다. 최근 들어 활발한 연구가 이루어지고 있는 고빈도(high frequency) 자료에 기초한 변동성 측정방법을 국내 주가에 적용시켜 1분 단위 고빈도 주가로부터 일별 변동성을 계산하였다. 또한, 모형 기반 방법인 GARCH와 자료 기반 방법인 역사적 변동성(historical volatility)을 융합하여 새로운 변동성 측정법을 제안하였다.

Keywords

References

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  2. Choice of weights in a hybrid volatility based on high-frequency realized volatility vol.29, pp.3, 2016, https://doi.org/10.5351/KJAS.2016.29.3.505